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Tech Policy Press: Unpacking New NIST Guidance on AI
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This article is useful for tracking US federal AI governance milestones; the NIST documents it covers are key voluntary frameworks shaping responsible AI development practices in the US.
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Summary
Tech Policy Press analyzes the suite of NIST publications released at the 270-day deadline of Biden's 2023 AI Executive Order, covering the finalized AI Risk Management Framework Generative AI Profile (NIST AI 600-1), secure software development guidance, AI standards reports, and a new testing platform called Dioptra. The article summarizes each document's scope, key risk categories, and voluntary guidelines aimed at improving AI safety, security, and trustworthiness. It serves as an accessible entry point for understanding the policy landscape emerging from the EO.
Key Points
- •NIST released final reports on generative AI risks, secure software, and AI standards as part of the Biden EO's 270-day deadline on July 26, 2024.
- •The AI RMF Generative AI Profile (NIST AI 600-1) provides 200+ voluntary actions across 12 risk categories for managing generative AI risks.
- •US AI Safety Institute published draft guidance to help software developers mitigate risks from generative AI and dual-use foundation models.
- •Dioptra, a new NIST testing platform, helps AI developers measure how adversarial attacks degrade AI system performance.
- •All guidance is voluntary, aimed at balancing innovation support with safety and trustworthiness improvements.
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| Page | Type | Quality |
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| NIST and AI Safety | Organization | 63.0 |
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Unpacking New NIST Guidance on Artificial Intelligence | TechPolicy.Press Unpacking New NIST Guidance on Artificial Intelligence
Gabby Miller / Aug 2, 2024
President Joe Biden announcing his Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence on Oct. 30, 2023. Source: The White House .
Last Friday marked the 270-day deadline for a raft of publications released by the National Institute of Standards and Technology (NIST) as part of US President Joe Biden’s 2023 executive order on artificial intelligence. The publications provide voluntary guidelines for AI developers to “improve the safety, security and trustworthiness” of their systems and aim to mitigate generative AI-specific risks while continuing to support innovation.
The down-to-the-wire rollout included final reports on generative AI , secure software , and AI standards , some of which are follow-ups to draft reports NIST released in the spring. NIST published two additional products, including a draft guidance document from the US AI Safety Institute (AISI) meant to help software developers mitigate risks stemming from generative AI and dual-use foundation models, as well as a novel testing platform, called Dioptra, to help AI system developers measure how certain attacks degrade their AI systems’ performance.
Related Reading:
NIST Unveils Draft Guidance Reports Following Biden's AI Executive Order
Five Takeaways from the NIST AI Risk Management Framework
Reconciling Agile Development With AI Safety
Summaries of each NIST document or product published on July 26, 2024 can be found below.
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
The final version of NIST’s AI Risk Management Framework Generative AI Profile (RMF GAI, NIST AI 600-1) was published on Friday. The initial draft was publicly released in January 2023, and underwent several draft versions that took into account public comments, workshops, and other opportunities for feedback. It’s meant to be a companion resource to NIST’s more comprehensive Risk Management Framework (RMF), and help organizations identify and propose actions for generative AI risks. It provides more than 200 actions across twelve different risk categories for AI developers to consider when managing risks. In March, NIST launched the Trustworthy and Responsible AI Resource Center to implement, operationalize, and facilitate international alignment with the AI RMF.
This twelve risk categories include:
Chemical, Biological, Radiological, and Nuclear (CBRN) Information or Capabilities
Confabulation, or “hallucination”
Dangerous, Violent, or Hateful Content
Data Privacy
Environmental Impacts
Harmful Bias and Homogenization
Human-AI Configuration
Information Integrity
Information Security
Intellectual Property
Obscene, Degrading, and/or Abusive Content
Value Chain and Component Integration
NIST defines risk in this context a
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